한의학에서 딥러닝의 뜻밖의 역할: 딥러닝의 과학으로 한의학 이해하기
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 배효진 | - |
dc.contributor.author | 김창업 | - |
dc.date.accessioned | 2024-01-06T02:00:23Z | - |
dc.date.available | 2024-01-06T02:00:23Z | - |
dc.date.issued | 2023-03 | - |
dc.identifier.issn | 2714-0237 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/89961 | - |
dc.description.abstract | Deep learning is revolutionizing in many scientific fields today. When it comes to Traditional Korean Medicine(TKM), it is commonly expected that deep learning will be able to assist TKM doctors to diagnose and prescribe treatments. We believe, however, there is another way to revolutionize TKM using deep learning. Mathematically, deep learning is a universal approximation function and can be a powerful model that explains cognitive processes in the brain. Since all of the decision-making processes in TKM are cognitive processes in the TKM doctors’ brain, they could also be modeled and explained using deep learning framework. As the science of deep learning advances, we will be able to better understand TKM through deep learning framework. | - |
dc.format.extent | 7 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | 대한미병의학회 | - |
dc.title | 한의학에서 딥러닝의 뜻밖의 역할: 딥러닝의 과학으로 한의학 이해하기 | - |
dc.title.alternative | The Unexpected Role of Deep Learning in Traditional Korean Medicine (TKM): The Science of Deep Learning Can Help better Understand TKM | - |
dc.type | Article | - |
dc.identifier.doi | 10.37928/kjsm.2023.4.1.44 | - |
dc.identifier.bibliographicCitation | 대한미병의학회지, v.4, no.1, pp 44 - 50 | - |
dc.identifier.kciid | ART003035269 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 50 | - |
dc.citation.startPage | 44 | - |
dc.citation.title | 대한미병의학회지 | - |
dc.citation.volume | 4 | - |
dc.citation.number | 1 | - |
dc.publisher.location | 대한민국 | - |
dc.subject.keywordAuthor | Deep learning | - |
dc.subject.keywordAuthor | Artificial intelligence (AI) | - |
dc.subject.keywordAuthor | Traditional Korean medicine (TKM) | - |
dc.subject.keywordAuthor | Pattern differentiation | - |
dc.description.journalRegisteredClass | kciCandi | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.